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 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 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.

scholarly journals The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing

2021 ◽  
Vol 10 (7) ◽  
pp. 479
Author(s):  
Yihang Li ◽  
Liyan Xu
Keyword(s):  
Prevention And Control ◽  
Control Period ◽  
Flow Patterns ◽  
Control Measures ◽  
Pedestrian Flow ◽  
Prevention Measures ◽  
Government Control ◽  
Functional Categories ◽  
And Control ◽  
The Impact

The COVID-19 pandemic is a major challenge for society as a whole, and analyzing the impact of the spread of the epidemic and government control measures on the travel patterns of urban residents can provide powerful help for city managers to designate top-level epidemic prevention policies and specific epidemic prevention measures. This study investigates whether it is more appropriate to use groups of POIs with similar pedestrian flow patterns as the unit of study rather than functional categories of POIs. In this study, we analyzed the hour-by-hour pedestrian flow data of key locations in Beijing before, during, and after the strict epidemic prevention and control period, and we found that the pedestrian flow patterns differed greatly in different periods by using a composite clustering index; we interpreted the clustering results from two perspectives: groups of pedestrian flow patterns and functional categories. The results show that depending on the specific stage of epidemic prevention and control, the number of unique pedestrian flow patterns decreased from four before the epidemic to two during the strict control stage and then increased to six during the initial resumption of work. The restrictions on movement are correlated with most of the visitations, and the release of restrictions led to an increase in the variety of unique pedestrian flow patterns compared to that in the pre-restriction period, even though the overall number of visitations decreased, indicating that social restrictions led to differences in the flow patterns of POIs and increased social distance.

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 Coordinated Management of COVID-19 Response: Lessons From Whole-of-Society and Whole-of-Health Strategies in Wuhan, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Shanquan Chen ◽  
Pan Zhang ◽  
Yun Zhang ◽  
Hong Fung ◽  
Yong Han ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Health Care Delivery ◽  
Prevention And Control ◽  
Care Delivery ◽  
Control Strategies ◽  
Control Period ◽  
Targeted Prevention ◽  
First Line ◽  
And Control

Background: The outbreak of novel coronavirus disease 2019 (COVID-19) has been challenging globally following the scarcity of medical resources after a surge in demand. As the pandemic continues, the question remains on how to accomplish more with the existing resources and improve the efficiency of existing health care delivery systems worldwide. In this study, we reviewed the experience from Wuhan - the first city to experience a COVID-19 outbreak – that has presently shown evidence for efficient and effective local control of the epidemic.Material and Methods: We performed a retrospective qualitative study based on the document analysis of COVID-19-related materials and interviews with first-line people in Wuhan.Results: We extracted two themes (the evolution of Wuhan's prevention and control strategies on COVID-19 and corresponding effectiveness) and four sub-themes (routine prevention and control period, exploration period of targeted prevention and control strategies, mature period of prevention and control strategies, and recovery period). How Wuhan combatted COVID-19 through multi-tiered and multi-sectoral collaboration, overcoming its fragmented, hospital-centered, and treatment-dominated healthcare system, was illustrated and summarized.Conclusion: Four lessons for COVID-19 prevention and control were summarized: (a) Engage the communities and primary care not only in supporting but also in screening and controlling, and retain community and primary care as among the first line of COVID-19 defense; (b) Extend and stratify the existing health care delivery system; (c) Integrate person-centered integrated care into the whole coordination; and (d) Delink the revenue relationship between doctors and patients and safeguard the free-will of physicians when treating patients.

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