电子科技大学学报最新文献_第4页

湿性年龄相关性黄斑变性血浆代谢组学研究湿性年龄相关性黄斑变性血浆代谢组学研究

电子科技大学学报 Pub Date : 2021-01-01 DOI: 10.27005/d.cnki.gdzku.2021.000704

邓燕辉

引用次数: 0

Inferring the Trend of COVID-19 Epidemic with Close Contacts Counting 用密切接触者计数推断新冠肺炎疫情发展趋势

电子科技大学学报 Pub Date : 2020-09-30 DOI: 10.12178/1001-0548.2020263

Suoyi Tan, Z. Cao, Shuo Qin, Saran Chen, B. Sai, S. Guo, Chu Chu Liu, Mengsi Cai, Tao Zhou, Wei Zhang, Xin Lu

引用次数: 1

Quantitative Evaluation on the Prevention and Control Efficacy of COVID-19 新冠肺炎防控效果的定量评价

电子科技大学学报 Pub Date : 2020-05-30 DOI: 10.12178/1001-0548.4_2020144

Duanbing Chen, Wei Bai, Yan Wang, Min Wang, Wujuan Yu, Tao Zhou

引用次数: 1

Nursing Role Results in Higher Susceptibility of Women: Analyzing Family Clusters during COVID-19 Outbreaks 护理作用导致女性易感性增加:COVID-19暴发期间家庭聚集性分析

电子科技大学学报 Pub Date : 2020-05-30 DOI: 10.12178/1001-0548.16_2020201

J. Liao, Z. Yang, Tao Zhou

引用次数: 1

Epidemiological Characteristics of Novel Coronavirus COVID-19 Based on Web Data Mining 基于Web数据挖掘的新型冠状病毒COVID-19流行病学特征

电子科技大学学报 Pub Date : 2020-05-30 DOI: 10.12178/1001-0548.14_2020079

Wen Zheng, Cai Zhao, Z. Li, X. Wu, Tao Hu

{"title":"Epidemiological Characteristics of Novel Coronavirus COVID-19 Based on Web Data Mining","authors":"Wen Zheng, Cai Zhao, Z. Li, X. Wu, Tao Hu","doi":"10.12178/1001-0548.14_2020079","DOIUrl":"https://doi.org/10.12178/1001-0548.14_2020079","url":null,"abstract":"Based on the Selenium data mining technology, the epidemiological characteristics of real help cases in Sina Weibo were obtained by the analysis of 690 valid cases posted in the Sina Weibo “Pneumonia Patients Asking for Help” topic from February 4 to February 22, 2020. The research showed that 97.6% of the patients seeking for help came from Wuhan, mainly centralized in Wuchang, Tongkou, Hanyang etc. urban areas, and the proportion is directly proportional to the local medical resources and population density. The cases of Weibo help were mainly distributed from February 4 to February 7, 2020. With the relief of medical resources, the number of cases seeking help through social media decreased significantly. The distribution of patients, whose diagnosed date was mainly from January 16 to February 6, 2020, was basically consistent with the case information released by the Chinese Center for Disease Control and Prevention (CCDC). The median age of patients seeking for help was 60 years old, which was much higher than the data released by the CCDC but was roughly coincident with the data of the central hospital of Wuhan. The results of this study indicate that when dealing with major outbreaks of infectious diseases, social media are equally important in epidemiological analysis as well as the role in the dissemination of public opinion. Based on the wide adoption and timeliness nature of social media, it will be helpful for decision-makers to quickly grasp the real-world situation as it is combined with data mining or big data analysis.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46888535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SEIR-Based COVID-19 Transmission Model and Inflection Point Prediction Analysis 基于SEIR的新冠肺炎传播模型及拐点预测分析

电子科技大学学报 Pub Date : 2020-05-01 DOI: 10.12178/1001-0548.9_2020029

Fan Ruguo, Wang Yi-bo, Luo Ming, Zhang Yingqing, Zhu Chao-ping

引用次数: 26

Analysis of Spread Dynamics of Coronavirus SARS-CoV-2, SARS-CoV and MERS-CoV 冠状病毒SARS-CoV-2、SARS-CoV和MERS-CoV的传播动态分析

电子科技大学学报 Pub Date : 2020-05-01 DOI: 10.12178/1001-0548.6_2020067

Liang Kai-hao, Zhang Wen-feng, Zhang Xiao-hua, WU Zhuo-kui, Liu Qin, Zhang Chao-long, Li Zi-long

引用次数: 2

Infection and Prevention of COVID-19 in Schools Based on Real-Life Interpersonal Contact Data 基于现实生活人际接触数据的学校新冠肺炎感染与预防

电子科技大学学报 Pub Date : 2020-05-01 DOI: 10.12178/1001-0548.13_2020172

Sun Hao-chen, Xu Ming-da, Xu Xiao-ke

{"title":"Infection and Prevention of COVID-19 in Schools Based on Real-Life Interpersonal Contact Data","authors":"Sun Hao-chen, Xu Ming-da, Xu Xiao-ke","doi":"10.12178/1001-0548.13_2020172","DOIUrl":"https://doi.org/10.12178/1001-0548.13_2020172","url":null,"abstract":"With the stabilization of the COVID-19 in China, the resumption of study has become the hottest issue most concerned by the people. The long-time gathering and face-to-face contact of students and teachers in schools increase the risk of their mutual infection. Although school suspension is generally considered to be the most feasible strategy to alleviate epidemics, large-scale isolation is often accompanied by high socio-economic costs and even social panic. Therefore, when an outbreak occurs in schools, we need to try to use more detailed scientific prevention and control measures. In this study, the spread of the COVID-19 in schools is simulated based on real interpersonal contact data, and the prevention and control measures are formulated by calculating the effective distance among students. This study finds that students have more contact with students in the same class and grade in schools. Therefore, when cases are found in schools, the development of the epidemic can be controlled by closing the patient's class and grade in time, and it will achieve similar or even better results than the closed school. In addition, in the absence of closure and the application of prevention and control measures, the impact of the proportion of asymptomatic patients and the incubation period infectivity in school outbreaks are analyzed, respectively. After the prevention and control measures are applied, the epidemic situation in each case will be controlled, and it will soon usher in a time when the epidemic situation improves. The research in this paper helps schools to select appropriate prevention and control measures, and accurately assess the impact of asymptomatic patients and incubation period infectivity on the epidemic.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47316880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Fitness of the Generalized Growth to the COVID-19 Data 广义增长对新冠肺炎数据的适应性

电子科技大学学报 Pub Date : 2020-05-01 DOI: 10.12178/1001-0548.5_2020037

Lin Zhang

引用次数: 3

The Geographical Destination Distribution and Effect of Outflow Population of Wuhan When the Outbreak of COVID-19 新冠肺炎暴发时武汉市人口外流的地理目的地分布及影响

电子科技大学学报 Pub Date : 2020-05-01 DOI: 10.12178/1001-0548.2_2020033

Xu Xiao-ke, Wen Cheng, Z. Guang-yao, Sun Hao-chen, Liu Bo, Wang Xian-wen

{"title":"The Geographical Destination Distribution and Effect of Outflow Population of Wuhan When the Outbreak of COVID-19","authors":"Xu Xiao-ke, Wen Cheng, Z. Guang-yao, Sun Hao-chen, Liu Bo, Wang Xian-wen","doi":"10.12178/1001-0548.2_2020033","DOIUrl":"https://doi.org/10.12178/1001-0548.2_2020033","url":null,"abstract":"In this paper, we provide a statistical analysis of population movements leaving Wuhan based on mass population movement information which is collected by geographic services of Tencent and Baidu. Firstly, we find that the five million people leaving Wuhan before the official announcement that they will close the exits are not much different from the normal population movement during the previous Spring Festival travel rush. However, small portion of the population poured out of Wuhan in the last period before the exits closed. Secondly, according to statistics of the destination cities of the outflow population from Wuhan starting from 2020, we find that the destination distribution of folks in 2020 was basically same as that in previous years. Finally, the influence of the population leaving Wuhan on epidemic spread is analyzed. We find that the role of incubation period must be considered when measuring this influence. This study is helpful for relevant personnel to grasp the speed of epidemic spread, assess the risk of epidemic, and provides reference to predict and stop disease spreading.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48881599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8