Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie
{"title":"Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China.","authors":"Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie","doi":"10.4081/gh.2024.1255","DOIUrl":"10.4081/gh.2024.1255","url":null,"abstract":"<p><p>Individuals migrating with chronic diseases often face substantial health risks, and their patterns of healthcare-seeking behavior are commonly influenced by mobility. However, to our knowledge, no research has used spatial statistics to verify this phenomenon. Utilizing data from the China Migrant Dynamic Survey of 2017, we conducted a geostatistical analysis to identify clusters of chronic disease patients among China's internal migrants. Geographically weighted regressions were utilized to examine the driving factors behind the reasons why treatment was not sought by 711 individuals among a population sample of 9272 migrant people with chronic diseases. The results indicate that there is a spatial correlation in the clustering of internal migrants with chronic diseases in China. The prevalence is highly clustered in Zhejiang and Xinjiang in north-eastern China. Hotspots were found in the northeast (Jilin and Liaoning), the north (Hebei, Beijing, and Tianjin), and the east (Shandong) and also spread into surrounding provinces. The factors that affect the migrants with no treatment were found to be the number of hospital beds per thousand population, the per capita disposable income of medical care, and the number of participants receiving health education per 1000 Chinese population. To rectify this situation, the local government should \"adapt measures to local conditions.\" Popularizing health education and coordinating the deployment of high-quality medical facilities and medical workers are effective measures to encourage migrants to seek reasonable medical treatment.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141158966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carlos Matías Scavuzzo, Micaela Natalia Campero, Rosana Elizabeth Maidana, María Georgina Oberto, María Victoria Periago, Ximena Porcasi
{"title":"Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina.","authors":"Carlos Matías Scavuzzo, Micaela Natalia Campero, Rosana Elizabeth Maidana, María Georgina Oberto, María Victoria Periago, Ximena Porcasi","doi":"10.4081/gh.2024.1279","DOIUrl":"10.4081/gh.2024.1279","url":null,"abstract":"<p><p>Argentina has a heterogeneous prevalence of infections by intestinal parasites (IPs), with the north in the endemic area, especially for soil-transmitted helminths (STHs). We analyzed the spatial patterns of these infections in the city of Tartagal, Salta province, by an observational, correlational, and cross-sectional study in children and adolescents aged 1 to 15 years from native communities. One fecal sample per individual was collected to detect IPs using various diagnostic techniques: Telemann sedimentation, Baermann culture, and Kato-Katz. Moran's global and local indices were applied together with SaTScan to assess the spatial distribution, with a focus on cluster detection. The extreme gradient boosting (XGBoost) machine-learning model was used to predict the presence of IPs and their transmission pathways. Based on the analysis of 572 fecal samples, a prevalence of 78.3% was found. The most frequent parasite was Giardia lamblia (30.9%). High- and low-risk clusters were observed for most species, distributed in an east-west direction and polarized in two large foci, one near the city of Tartagal and the other in the km 6 community. Spatial XGBoost models were obtained based on distances with a minimum median accuracy of 0.69. Different spatial patterns reflecting the mechanisms of transmission were noted. The distribution of the majority of the parasites studied was aligned in a westerly direction close to the city, but the STH presence was higher in the km 6 community, toward the east. The purely spatial analysis provides a different and complementary overview for the detection of vulnerable hotspots and strategic intervention. Machine-learning models based on spatial variables explain a large percentage of the variability of the IPs.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141158967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter M Macharia, Kerry L M Wong, Lenka Beňová, Jia Wang, Prestige Tatenda Makanga, Nicolas Ray, Aduragbemi Banke-Thomas
{"title":"Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations.","authors":"Peter M Macharia, Kerry L M Wong, Lenka Beňová, Jia Wang, Prestige Tatenda Makanga, Nicolas Ray, Aduragbemi Banke-Thomas","doi":"10.4081/gh.2024.1266","DOIUrl":"10.4081/gh.2024.1266","url":null,"abstract":"<p><p>Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API's in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141156092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evangelos Melidoniotis, Kleomenis Kalogeropoulos, Andreas Tsatsaris, Michail Zografakis-Sfakianakis, George Lazopoulos, Nikolaos Tzanakis, Ioannis Anastasiou, Emmanouil Skalidis
{"title":"Geospatial epidemiology of coronary artery disease treated with percutaneous coronary intervention in Crete, Greece","authors":"Evangelos Melidoniotis, Kleomenis Kalogeropoulos, Andreas Tsatsaris, Michail Zografakis-Sfakianakis, George Lazopoulos, Nikolaos Tzanakis, Ioannis Anastasiou, Emmanouil Skalidis","doi":"10.4081/gh.2024.1251","DOIUrl":"10.4081/gh.2024.1251","url":null,"abstract":"<p><p>Coronary artery disease (CAD) constitutes a leading cause of morbidity and mortality worldwide. Percutaneous coronary intervention (PCI) is indicated in a significant proportion of CAD patients, either to improve prognosis or to relieve symptoms not responding to optimal medical therapy. Thus the annual number of patients undergoing PCI in a given geographical area could serve as a surrogate marker of the total CAD burden there. The aim of this study was to analyze the potential, spatial patterns of PCItreated CAD patients in Crete. We evaluated data from all patients subjected to PCI at the island's sole reference centre for cardiac catheterization within a 4-year study period (2013-2016). The analysis focused on regional variations of yearly PCI rates, as well as on the effect of several clinical parameters on the severity of the coronary artery stenosis treated with PCI across Crete. A spatial database within the ArcGIS environment was created and an analysis carried out based on global and local regression using ordinary least squares (OLS) and geographically weighted regression (GWR), respectively. The results revealed significant inter-municipality variation in PCI rates and thus potentially CAD burden, while the degree and direction of correlation between key clinical factors to coronary stenosis severity demonstrated specific geographical patterns. These preliminary results could set the basis for future research, with the ultimate aim to facilitate efficient healthcare strategies planning.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140945175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aleya Khalifa, Byoungjun Kim, Seann Regan, Tyrone Moline, Basile Chaix, Yen-Tyng Chen, John Schneider, Dustin T Duncan
{"title":"Examination of multidimensional geographic mobility and sexual behaviour among Black cisgender sexually minoritized men in Chicago.","authors":"Aleya Khalifa, Byoungjun Kim, Seann Regan, Tyrone Moline, Basile Chaix, Yen-Tyng Chen, John Schneider, Dustin T Duncan","doi":"10.4081/gh.2024.1273","DOIUrl":"10.4081/gh.2024.1273","url":null,"abstract":"<p><p>Black sexually minoritized men (BSMM) are the most likely to acquire HIV in Chicago- a racially segregated city where their daily travel may confer different HIV-related risks. From survey and GPS data among participants of the Neighbourhoods and Networks Cohort Study, we examined spatial (proportion of total activity space away from home), temporal (proportion of total GPS points away from home), and motivation-specific (discordance between residential and frequented sex or socializing neighbourhoods) dimensions of mobility. To identify potential drivers of BSMM's risk, we then examined associations between mobility and sexual behaviours known to cause HIV transmission: condomless anal sex, condomless anal sex with a casual partner, transactional sex, group sex, and sex-drug use. Multivariable logistic regression models assessed associations. Of 269 cisgender BSMM, most were 20-29 years old, identified as gay, and lowincome. On average, 96.9% (Standard Deviation: 3.7%) of participants' activity space and 53.9% (Standard Deviation: 38.1%) of participants' GPS points occurred outside their 800m home network buffer. After covariate adjustment, those who reported sex away from home were twice as likely to report condomless sex (Odds Ratio: 2.02, [95% Confidence Interval (CI): 1.08, 3.78]). Those who reported socializing away from home were four times more likely to have condomless sex with a casual partner (Odds Ratio: 4.16 [CI: 0.99, 29.0]). BSMM are on the move in Chicago, but only motivation-specific mobility may increase HIV transmission risk. Multidimensional investigations of mobility can inform place-based strategies for HIV service delivery.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140944888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Micaela Natalia Campero, Carlos Matías Scavuzzo, Carlos Marcelo Scavuzzo, María Dolores Román
{"title":"Spatial pattern analysis of the impact of community food environments on foetal macrosomia, preterm births and low birth weight.","authors":"Micaela Natalia Campero, Carlos Matías Scavuzzo, Carlos Marcelo Scavuzzo, María Dolores Román","doi":"10.4081/gh.2024.1249","DOIUrl":"10.4081/gh.2024.1249","url":null,"abstract":"<p><p>Community food environments (CFEs) have a strong impact on child health and nutrition and this impact is currently negative in many areas. In the Republic of Argentina, there is a lack of research evaluating CFEs regionally and comprehensively by tools based on geographic information systems (GIS). This study aimed to characterize the spatial patterns of CFEs, through variables associated with its three dimensions (political, individual and environmental), and their association with the spatial distribution in urban localities in Argentina. CFEs were assessed in 657 localities with ≥5,000 inhabitants. Data on births and CFEs were obtained from nationally available open-source data and through remote sensing. The spatial distribution and presence of clusters were assessed using hotspot analysis, purely spatial analysis (SaTScan), Moran's Index, semivariograms and spatially restrained multivariate clustering. Clusters of low risk for LBW, macrosomia, and preterm births were observed in the central-east part of the country, while high-risk clusters identified in the North, Centre and South. In the central-eastern region, low-risk clusters were found coinciding with hotspots of public policy coverage, high night-time light, social security coverage and complete secondary education of the household head in areas with low risk for negative outcomes of the birth variables studied, with the opposite with regard to households with unsatisfied basic needs and predominant land use classes in peri-urban areas of crops and herbaceous cover. These results show that the exploration of spatial patterns of CFEs is a necessary preliminary step before developing explanatory models and generating novel findings valuable for decision-making.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140878033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jerry Enoe, Michael Sutherland, Dexter Davis, Bheshem Ramlal, Charisse Griffith-Charles, Keston H Bhola, Elsai Mati Asefa
{"title":"A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment.","authors":"Jerry Enoe, Michael Sutherland, Dexter Davis, Bheshem Ramlal, Charisse Griffith-Charles, Keston H Bhola, Elsai Mati Asefa","doi":"10.4081/gh.2024.1264","DOIUrl":"10.4081/gh.2024.1264","url":null,"abstract":"<p><p>Although previous studies have acknowledged the potential of geographic information systems (GIS) and social media data (SMD) in assessment of exposure to various environmental risks, none has presented a simple, effective and user-friendly tool. This study introduces a conceptual model that integrates individual mobility patterns extracted from social media, with the geographic footprints of infectious diseases and other environmental agents utilizing GIS. The efficacy of the model was independently evaluated for selected case studies involving lead in the ground; particulate matter in the air; and an infectious, viral disease (COVID- 19). A graphical user interface (GUI) was developed as the final output of this study. Overall, the evaluation of the model demonstrated feasibility in successfully extracting individual mobility patterns, identifying potential exposure sites and quantifying the frequency and magnitude of exposure. Importantly, the novelty of the developed model lies not merely in its efficiency in integrating GIS and SMD for exposure assessment, but also in considering the practical requirements of health practitioners. Although the conceptual model, developed together with its associated GUI, presents a promising and practical approach to assessment of the exposure to environmental risks discussed here, its applicability, versatility and efficacy extends beyond the case studies presented in this study.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140320012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Behzad Kiani, Benn Sartorius, Colleen L Lau, Robert Bergquist
{"title":"Mastering geographically weighted regression: key considerations for building a robust model.","authors":"Behzad Kiani, Benn Sartorius, Colleen L Lau, Robert Bergquist","doi":"10.4081/gh.2024.1271","DOIUrl":"10.4081/gh.2024.1271","url":null,"abstract":"<p><p>Geographically weighted regression (GWR) takes a prominent role in spatial regression analysis, providing a nuanced perspective on the intricate interplay of variables within geographical landscapes (Brunsdon et al., 1998). However, it is essential to have a strong rationale for employing GWR, either as an addition to, or a complementary analysis alongside, non-spatial (global) regression models (Kiani, Mamiya et al., 2023). Moreover, the proper selection of bandwidth, weighting function or kernel types, and variable choices constitute the most critical configurations in GWR analysis (Wheeler, 2021). [...].</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qiong Zhang, Shangrui Zhu, Sue C Grady, Anqi Wang, Hollis Hutchings, Jessica Cox, Andrew Popoff, Ikenna Okereke
{"title":"Spatial and spatio-temporal clusters of lung cancer incidence by stage of disease in Michigan, United States 1985-2018.","authors":"Qiong Zhang, Shangrui Zhu, Sue C Grady, Anqi Wang, Hollis Hutchings, Jessica Cox, Andrew Popoff, Ikenna Okereke","doi":"10.4081/gh.2024.1219","DOIUrl":"10.4081/gh.2024.1219","url":null,"abstract":"<p><p>Lung cancer is the most common cause of cancer-related death in Michigan. Most patients are diagnosed at advanced stages of the disease. There is a need to detect clusters of lung cancer incidence over time, to generate new hypotheses about causation and identify high-risk areas for screening and treatment. The Michigan Cancer Surveillance database of individual lung cancer cases, 1985 to 2018 was used for this study. Spatial and spatiotemporal clusters of lung cancer and level of disease (localized, regional and distant) were detected using discrete Poisson spatial scan statistics at the zip code level over the study time period. The approach detected cancer clusters in cities such as Battle Creek, Sterling Heights and St. Clair County that occurred prior to year 2000 but not afterwards. In the northern area of the lower peninsula and the upper peninsula clusters of late-stage lung cancer emerged after year 2000. In Otter Lake Township and southwest Detroit, late-stage lung cancer clusters persisted. Public and patient education about lung cancer screening programs must remain a health priority in order to optimize lung cancer surveillance. Interventions should also involve programs such as telemedicine to reduce advanced stage disease in remote areas. In cities such as Detroit, residents often live near industry that emits air pollutants. Future research should therefore, continue to focus on the geography of lung cancer to uncover place-based risks and in response, the need for screening and health care services.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139736796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo
{"title":"Spatial-temporal risk factors in the occurrence of rabies in Mexico.","authors":"Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo","doi":"10.4081/gh.2024.1245","DOIUrl":"10.4081/gh.2024.1245","url":null,"abstract":"<p><p>Rabies is a zoonotic disease that affects livestock worldwide. The distribution of rabies is highly correlated with the distribution of the vampire bat Desmodus rotundus, the main vector of the disease. In this study, climatic, topographic, livestock population, vampire distribution and urban and rural zones were used to estimate the risk for presentation of cases of rabies in Mexico by co- Kriging interpolation. The highest risk for the presentation of cases is in the endemic areas of the disease, i.e. the States of Yucatán, Chiapas, Campeche, Quintana Roo, Tabasco, Veracruz, San Luis Potosí, Nayarit and Baja California Sur. A transition zone for cases was identified across northern Mexico, involving the States of Sonora, Sinaloa, Chihuahua, and Durango. The variables topography, vampire distribution, bovine population and rural zones are the most important to explain the risk of cases in livestock. This study provides robust estimates of risk and spread of rabies based on geostatistical methods. The information presented should be useful for authorities responsible of public and animal health when they plan and establish strategies preventing the spread of rabies into rabies-free regions of México.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139576488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}