scholarly journals Tuberculosis in Epidemic Prevention and Control Based on Big Data Technology

2021 ◽  
Vol 1881 (4) ◽  
pp. 042036
Author(s):  
Jiao Tan ◽  
Yonghong Ma ◽  
Ke Men ◽  
Jing Lei ◽  
Hairui Zhang ◽  
...  
Keyword(s):  
Big Data ◽  
Prevention And Control ◽  
And Control ◽  
Big Data Technology

scholarly journals Application of Big Data Technology in the Fight Against New Coronary Pneumonia Epidemic in China

2021 ◽  
Author(s):  
Xie Yan
Keyword(s):  
Big Data ◽  
Policy Implementation ◽  
Prevention And Control ◽  
Control Period ◽  
Vital Role ◽  
Great Success ◽  
Dynamic Information ◽  
Epidemic Dynamic ◽  
And Control ◽  
Big Data Technology

In the fight against New Coronary Pneumonia Epidemic, Chinese Ministry of Health put forward the inevitable requirements of precise policy implementation and scientific epidemic prevention. Accordingly, the big data technology has been applied in the analysis of epidemic dynamic, information inquiry, disease prevention and treatment, and prediction of epidemic trend. And, great success has been achieved in the fight, where the big data technology has played a vital role. This article outlines the main applications of big data technology in the prevention and control of New Coronary Pneumonia Epidemic, and proposes suggestions based on the problems in the application of big data during the epidemic prevention and control period. In the later stage, the integration of big data technology in various fields should be accelerated, information should be further shared and the utility value of data should be maximized.

scholarly journals Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations (Preprint)

2020 ◽  
Author(s):  
Jun Wu ◽  
Jian Wang ◽  
Stephen Nicholas ◽  
Elizabeth Maitland ◽  
Qiuyan Fan
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Infectious Diseases ◽  
Prevention And Control ◽  
Data Application ◽  
Wide Range ◽  
Low Efficiency ◽  
And Control ◽  
Collection Methods ◽  
Big Data Technology

BACKGROUND In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease’s rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. OBJECTIVE The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. METHODS We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China’s new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China’s response to the epidemic and to provide lessons for other countries’ prevention and control of COVID-19. RESULTS In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus’s sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. CONCLUSIONS China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.

scholarly journals Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations

10.2196/21980 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e21980
Author(s):  
Jun Wu ◽  
Jian Wang ◽  
Stephen Nicholas ◽  
Elizabeth Maitland ◽  
Qiuyan Fan
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Infectious Diseases ◽  
Prevention And Control ◽  
Data Application ◽  
Wide Range ◽  
Low Efficiency ◽  
And Control ◽  
Collection Methods ◽  
Big Data Technology

Background In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease’s rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. Objective The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. Methods We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China’s new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China’s response to the epidemic and to provide lessons for other countries’ prevention and control of COVID-19. Results In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus’s sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. Conclusions China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.

Off-office audit of natural resource assets and water pollution: a quasi-natural experiment in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaowei Ma ◽  
Muhammad Shahbaz ◽  
Malin Song
Keyword(s):  
Water Pollution ◽  
Big Data ◽  
Water Resources ◽  
Natural Resource ◽  
Prevention And Control ◽  
Industrial Structure ◽  
Dynamic Effect ◽  
Content Type ◽  
Audit System ◽  
And Control

PurposeThe purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.Design/methodology/approachThis study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.FindingsThe implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.Practical implicationsThese findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.Originality/valueThis study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

scholarly journals Reflection on Prevention and Control of Telecommunication Network Fraud in Big Data Era

2020 ◽  
Vol 2 (2) ◽  
pp. 42
Author(s):  
Xingrui Wang
Keyword(s):  
Big Data ◽  
Communication Technology ◽  
Telecommunication Network ◽  
Rapid Development ◽  
Economic Losses ◽  
The Public ◽  
Telecommunication Equipment ◽  
The Masses ◽  
And Control ◽  
Big Data Technology

<p>With the rapid development of smart phones and communication technology, the frequency of communication between the public and society through telecommunication equipment is increasing. At the same time, some lawless elements often cheat the public through telecommunication equipment, which brings irreparable economic losses to the society and the masses to a certain extent. In view of the above problems, this article takes the source of telecommunication fraud as the breakthrough point, analyzes the existing telecommunication fraud processing technology and points out its shortcomings, and then proposes a method of telephone fraud analysis based on big data technology. This technology fills the defects of the existing telecommunication interception technology and provides a new idea for effectively avoiding telecommunication fraud in the future.</p>

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