Geospatial Health最新文献

Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases. 整合基于病原体的疾病、流动性和废水模型，以研究传染病的传播。

IF 1 4区医学

Geospatial Health Pub Date : 2025-02-11 DOI: 10.4081/gh.2025.1326

Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla

{"title":"Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases.","authors":"Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla","doi":"10.4081/gh.2025.1326","DOIUrl":"10.4081/gh.2025.1326","url":null,"abstract":"Wastewater-based epidemiology was utilized during the COVID-19 outbreak to monitor the circulation of SARS-CoV-2, the virus causing this disease. However, this approach is limited by the need for additional methods to accurately translate virus concentrations in wastewater to disease-positive human counts. Combined modelling of COVID-19 disease cases and the concentration of its causative virus, SARS-CoV-2, in wastewater will necessarily deepen our understanding. However, this requires addressing the technical differences between disease, population mobility and wastewater models. To that end, we developed an integrated Agent-Based Model (ABM) that facilitates analysis in space and time at various temporal resolutions, including disease spread, population mobility and wastewater production, while also being sufficiently generic for different types of infectious diseases or pathogens. The integrated model replicates the epidemic curve for COVID-19 and can estimate the daily infections at the household level, enabling the monitoring of the spatial patterns of infection intensity. Additionally, the model allows monitoring the estimated production of infected wastewater over time and spatially across the sewage and treatment plant. The model addresses differences between resolutions and can potentially support Early Warning Systems (EWS) for future pandemics.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143400935","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}

引用次数: 0

Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad. 绘制乍得西部梅奥-凯比省的牲畜系统、牛和山羊疾病地图。

IF 1 4区医学

Geospatial Health Pub Date : 2025-02-03 DOI: 10.4081/gh.2025.1365

Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng

{"title":"Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad.","authors":"Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng","doi":"10.4081/gh.2025.1365","DOIUrl":"10.4081/gh.2025.1365","url":null,"abstract":"This study aimed to compile an inventory of the main diseases affecting these species in Mayo-Kebbi Ouest Province in Chad. A survey was conducted between 6 May and 7 August 2024 using a cascade data collection method identifying 310 farmers and 19 veterinarians with an average of 10 to 12 years of experience in advising and supporting livestock practices The data collected included socio-professional characteristics of participants, livestock practices, and geospatial information. These data were managed in Excel and analysed with R. The analysis involved descriptive and inferential statistical techniques including binary logistic regression resulting in maps illustrating disease hotspots and livestock systems. Thematic maps, tables and charts with a 5% significance threshold visualised risk areas and associated livestock practices. The results show a predominance of male farmers (91.9%) from 20 different ethnic groups. The livestock systems identified include data on farming divided into extensive (14.8%), mixed (0.3%) and semi-intensive farming (84.8%). On average, farms have 41 cattle and 25 goats. Animal diseases were found to cause 29.5% reduction in herd productivity. Transhumance (p=0.000356) and animal disease incidence (p=0.03) were observed as significant risk factors associated with the abandonment of livestock farming. The main diseases recorded in cattle include contagious bovine pleuropneumonia (11.3%), bovine tuberculosis (2.5%), foot-and-mouth disease (45.0%), bluetongue (1.7%) and disease with symptoms reminiscent of rinderpest (2.5%). For goats, notable diseases include brucellosis (3.8%), lumpy skin disease (19.2%), goat plague (7.9%) and Rift Valley fever (6.3%). These findings confirm the importance of a geospatial epidemiological surveillance tool for monitoring animal diseases in this region.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143124265","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}

引用次数: 0

Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand. 泰国社会经济和卫生服务因素与抗生素自我用药的空间关联

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-27 DOI: 10.4081/gh.2025.1329

Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm, Warangkana Sungsitthisawad, Roshan Kumar Mahato

{"title":"Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand.","authors":"Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm, Warangkana Sungsitthisawad, Roshan Kumar Mahato","doi":"10.4081/gh.2025.1329","DOIUrl":"10.4081/gh.2025.1329","url":null,"abstract":"Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048825","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}

引用次数: 0

Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020. 2020年墨西哥2型糖尿病社会空间脆弱性指数

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-27 DOI: 10.4081/gh.2025.1348

Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen Del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez

{"title":"Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020.","authors":"Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen Del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez","doi":"10.4081/gh.2025.1348","DOIUrl":"10.4081/gh.2025.1348","url":null,"abstract":"This study aimed to estimate a socio-spatial vulnerability index for type 2 diabetes mellitus (T2DM) at the municipal level in Mexico for 2020. It incorporated factors such as poverty, social backwardness, marginalization index, and human development index. This retrospective ecological study analyzed 317,011 incident cases of T2DM in 2020. Utilizing multi-criteria decision analysis, weighted values were assigned to each vulnerability criterion. A multiple linear regression model was developed, complemented by cluster and outlier analyses using Moran I's and the high-low clustering method. A clustered spatial autocorrelation of high values was found across 17.65% of Mexico, which was statistically significant (p < 0.001). Conversely, 37.78% of the territory showed a pattern of low values without significant evidence of groupings. The analysis revealed 117 nodes of very high vulnerability forming six focal areas, 172 nodes with high vulnerability across five areas, 168 nodes with medium vulnerability in two areas, 112 nodes with low vulnerability across 16 areas, and 152 nodes with very low vulnerability in 24 focal areas. This method proves to be robust and offers a technical-scientific basis for guiding T2DM prevention strategies and actions using a spatial/epidemiological approach. It is recommended that future strategies take into account factors such as poverty, social backwardness, marginalization index, and human development index to be effective.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048822","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}

引用次数: 0

Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring. 基于时空监测的covid -19相关社区环境风险差异分析

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-04-28 DOI: 10.4081/gh.2025.1286

Jihong Zhang, Guohua Yin, Qiuhua Zhang, Juan Fang, Duo Jiang, Chao Yang, Na Sun

{"title":"Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring.","authors":"Jihong Zhang, Guohua Yin, Qiuhua Zhang, Juan Fang, Duo Jiang, Chao Yang, Na Sun","doi":"10.4081/gh.2025.1286","DOIUrl":"https://doi.org/10.4081/gh.2025.1286","url":null,"abstract":"The geo-inequality of COVID-19 risk has attracted a great deal of research attention. In this study, the spatial correlation between community environment and the incidence of COVID-19 cases in 30 Chinese cities is discussed. The spread of the disease is analyzed based on timing and spatial monitoring at the km2-grid level, with the use of publicly available data relating to housing prices, Gross Deomestic Product (GDP), medical facilities, consumer sites, public green spaces, and industrial sites. The results indicate substantial geographical variations in the distribution of COVID-19 communities in all 30 cities. Significant global bivariate spatial dependence was observed between the disease and housing prices (Moran's I =0.099, p<0.01, z=488.6), medical facilities (Moran's I = 0.349, p<0.01, z=1675.0), consumer sites (Moran's I =0.369, p<0.01, z=1843.4), green space (Moran's I =0.205, p<0.01, z=1037.8), and industrial sites (Moran's I =0.234, p<0.01, z=1178.6). The risk of COVID-19 under the influence of GDP is further examined for cities with per capita GDPs from high to low ranging from 1.69 to 4.62 (1.69~3.74~4.62, 95% CI). These findings provide greater detail on the interplay between the infectious disease and community environments.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144007918","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}

引用次数: 0

Sentiment analysis using a lexicon-based approach in Lisbon, Portugal. 在葡萄牙里斯本使用基于词典的方法进行情感分析。

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-04-24 DOI: 10.4081/gh.2025.1344

Iuria Betco, Ana Isabel Ribeiro, David S Vale, Luis Encalada-Abarca, Cláudia M Viana, Jorge Rocha

引用次数: 0

Spatial multilevel modelling male partners' influence on women's modern contraceptive use: a study in Angola and Zambia. 男性伴侣对女性现代避孕药具使用影响的空间多层次建模：安哥拉和赞比亚的研究。

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-05-12 DOI: 10.4081/gh.2025.1340

Kabeya Clement Mulamba

{"title":"Spatial multilevel modelling male partners' influence on women's modern contraceptive use: a study in Angola and Zambia.","authors":"Kabeya Clement Mulamba","doi":"10.4081/gh.2025.1340","DOIUrl":"https://doi.org/10.4081/gh.2025.1340","url":null,"abstract":"The main objective of this paper was to model the relationship between married women's contraceptive use and the influence of their male partners. The study took place in Angola and Zambia, which stems from the fact that these countries ratified the Maputo Protocol that emphasises promotion of reproductive health among women. Most previous studies investigating women's progress towards the realisation of what is advocated in this protocol have overlooked the role of the male partners. Hence, it has become imperative to reduce this gap in the literature. This paper discusses the application of spatial multilevel modelling, which incorporates two levels of information based on the nature of the data available. This approach acknowledges the hypothesis that contraceptive use is a social phenomenon occurring within the geographical space and is therefore susceptible to autocorrelation. Findings confirm that the level of influence of male partners' exertion on women's contraceptive use is dependent on the situation in the country where it takes place as shown by various study variables analysed. The results indicate that socioeconomic and education factors play a major role, a phenomenon that calls for tailor-made reproductive health policies considering these aspects.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144045072","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}

引用次数: 0

Impact of climate change on dengue fever: a bibliometric analysis. 气候变化对登革热的影响：文献计量学分析。

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-02-19 DOI: 10.4081/gh.2025.1301

Mai Liu, Yin Zhang

{"title":"Impact of climate change on dengue fever: a bibliometric analysis.","authors":"Mai Liu, Yin Zhang","doi":"10.4081/gh.2025.1301","DOIUrl":"10.4081/gh.2025.1301","url":null,"abstract":"Dengue is the most widespread and fastest-growing vectorborne disease worldwide. We employed bibliometric analysis to provide an overview of research on the impact of climate change on dengue fever focusing on both global and Southeast Asian regions. Using the Web of Science Core Collection (WoSCC) database, we reviewed studies on the impact of climate change on dengue fever between 1974 and 2022 taking into account study locations and international collaboration. The VOS viewer software (https://www.vosviewer.com/) and the Bibliometrix R package (https://www.bibliometrix.org/) were used to visualise country networks and keywords. We collected 2,055 relevant articles published globally between 1974 and 2022 on the impact of climate change on dengue fever, 449 of which published in Southeast Asia. Peaking in 2021, the overall number of publications showed a strong increase in the period 2000-2022. The United States had the highest number of publications (n=558) followed by China (261) and Brazil (228). Among the Southeast Asian countries, Thailand had most publications (n=123). Global and Southeast Asian concerns about the impact of climate change on dengue fever are essentially the same. They all emphasise the relationship between temperature and other climatic conditions on the one hand and the transmission of Aedes aegypti on the other. A significant positive correlation exists between the number of national publications and socioeconomic index and between international collaboration and scientific productivity in the field. Our study demonstrates the current state of research on the impact of climate change on dengue and provides a comparative analysis of the Southeast Asian region. Publication output in Southeast Asia lags behind that of major countries worldwide, and various strategies should be implemented to improve international collaboration, such as increasing the number of international collaborative projects and providing academic resources and research platforms for researchers.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460941","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}

引用次数: 0

Moran's I and Geary's C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases. Moran's I 和 Geary's C：调查空间权重矩阵对评估传染病分布的影响。

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-04-07 DOI: 10.4081/gh.2025.1277

Sarah Isnan, Ahmad Fikri Bin Abdullah, Abdul Rashid Shariff, Iskandar Ishak, Sharifah Norkhadijah Syed Ismail, Maheshwara Rao Appanan

{"title":"Moran's I and Geary's C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases.","authors":"Sarah Isnan, Ahmad Fikri Bin Abdullah, Abdul Rashid Shariff, Iskandar Ishak, Sharifah Norkhadijah Syed Ismail, Maheshwara Rao Appanan","doi":"10.4081/gh.2025.1277","DOIUrl":"10.4081/gh.2025.1277","url":null,"abstract":"The COVID-19 outbreak has precipitated severe occurrences on a global scale. Hence, spatial analysis is crucial in determining the relationships and patterns of geospatial data. Moran's I and Geary's C are prominent methodologies used to measure the spatial autocorrelation of geographical data. Both measure the degree of similarity or dissimilarity between nearby locations based on attribute values in such a way that the selection of distance techniques and weight matrices significantly impact the spatial autocorrelation results. This paper aimed at carrying out the spatial epidemiological characteristics analysis of the pandemic comparing the results of Moran's I and Geary's C with different parameters to gain a comprehensive understanding of the spatial relationship of COVID-19 cases. We employed distance-based techniques, K-nearest neighbour, and Queen contiguity techniques to assess the sensitivity of the different parameter configurations for both Moran's I and Geary's C. The findings revealed that former provided more reliable and robust results compared to the latter, with consistent results of spatial autocorrelation (positive spatial autocorrelation). The distance weight of 0.05 using the Manhattan method of Moran's I is the recommended distance weight, as it outperformed other weight matrices (Moran's I = 0.0152, Z-value= 110.8844 and p-value=0.001).","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143804832","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}

引用次数: 0

Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning. 地表温度预测慢性阻塞性肺病的死亡率：一项基于气候变量和影响机器学习的研究。

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-03-26 DOI: 10.4081/gh.2025.1319

Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist

{"title":"Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning.","authors":"Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist","doi":"10.4081/gh.2025.1319","DOIUrl":"10.4081/gh.2025.1319","url":null,"abstract":"Introduction: Chronic Obstructive Pulmonary Disease (COPD) mortality rates and global warming have been in the focus of scientists and policymakers in the past decade. The long-term shifts in temperature and weather patterns, commonly referred to as climate change, is an important public health issue, especially with regard to COPD.Method: Using the most recent county-level age-adjusted COPD mortality rates among adults older than 25 years, this study aimed to investigate the spatial trajectory of COPD in the United States between 2001 and 2020. Global Moran's I was used to investigate spatial relationships utilising data from Terra satellite for night-time land surface temperatures (LSTnt), which served as an indicator of warming within the same time period across the United States. The forest-based classification and regression model (FCR) was applied to predict mortality rates.Results: It was found that COPD mortality over the 20-year period was spatially clustered in certain counties. Moran's I statistic (I=0.18) showed that the COPD mortality rates increased with LSTnt, with the strongest spatial association in the eastern and south-eastern counties. The FCR model was able to predict mortality rates based on LSTnt values in the study area with a R2 value of 0.68.Conclusion: Policymakers in the United States could use the findings of this study to develop long-term spatial and health-related strategies to reduce the vulnerability to global warming of patients with acute respiratory symptoms.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143722936","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}

引用次数: 0