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 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 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 Prevention and Control of Pathogens Based on Big-Data Mining and Visualization Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Cui‐Xia Chen ◽  
Li‐Na Sun ◽  
Xue‐Xin Hou ◽  
Peng‐Cheng Du ◽  
Xiao‐Long Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Infectious Diseases ◽  
High Throughput Screening ◽  
Prevention And Control ◽  
Rapid Identification ◽  
Pathogenic Mechanisms ◽  
Visualization Analysis ◽  
Big Data Mining ◽  
And Control

Morbidity and mortality caused by infectious diseases rank first among all human illnesses. Many pathogenic mechanisms remain unclear, while misuse of antibiotics has led to the emergence of drug-resistant strains. Infectious diseases spread rapidly and pathogens mutate quickly, posing new threats to human health. However, with the increasing use of high-throughput screening of pathogen genomes, research based on big data mining and visualization analysis has gradually become a hot topic for studies of infectious disease prevention and control. In this paper, the framework was performed on four infectious pathogens (Fusobacterium, Streptococcus, Neisseria, and Streptococcus salivarius) through five functions: 1) genome annotation, 2) phylogeny analysis based on core genome, 3) analysis of structure differences between genomes, 4) prediction of virulence genes/factors with their pathogenic mechanisms, and 5) prediction of resistance genes/factors with their signaling pathways. The experiments were carried out from three angles: phylogeny (macro perspective), structure differences of genomes (micro perspective), and virulence and drug-resistance characteristics (prediction perspective). Therefore, the framework can not only provide evidence to support the rapid identification of new or unknown pathogens and thus plays a role in the prevention and control of infectious diseases, but also help to recommend the most appropriate strains for clinical and scientific research. This paper presented a new genome information visualization analysis process framework based on big data mining technology with the accommodation of the depth and breadth of pathogens in molecular level research.

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 SPECIES OF YEAST-LIKE FUNGI OF THE GENUS CANDIDA IN ISOLATES FROM THE ORAL CAVITY IN HIV-INFECTED PATIENTS OF THE BRYANSK REGION

2019 ◽  
pp. 57-60
Author(s):  
M.A. Mozzherova
Keyword(s):  
Oral Cavity ◽  
Infectious Diseases ◽  
Prevention And Control ◽  
Mixed Infections ◽  
And Control

We examined of the oral cavity of 174 HIV-infected patients who are on dispensary supervision and treatment in the Bryansk Center for the prevention and control of AIDS and infectious diseases with the implementation of a complex of bacteriological and parasitological studies. The predominance of non-albican species, as well as mixed infections with two or more species of fungi of the genus Candida were shown.

PRAWO ADMINISTRACYJNE WOBEC EPIDEMII CHOROBY ZAKAŹNEJ – WYBRANE PROBLEMY NA TLE STUDIUM PRZYPADKU KORONAWIRUSA SARSCOV-2 (CHOROBY COVID-19)

2021 ◽  
pp. 154-196
Author(s):  
Jacek Jagielski ◽  
Piotr Gołaszewski
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Prevention And Control ◽  
Administrative Law ◽  
Theoretical Terms ◽  
Digital Exclusion ◽  
Administrative Proceedings ◽  
And Control ◽  
Theoretical Reflection

The article discusses the legal and administrative regulations regarding the prevention and control of infectious diseases. The author puts forward and justifies the thesis that the SARS-CoV-2 coronavirus epidemic (COVID-19 disease) has exposed significant imperfections (and partly deficiencies) of the above-mentioned regulations, and at the same time revealed the effects of – sometimes insufficient – theoretical reflection on administrative law and the methods of reception of its assumptions and theoretical structures into the provisions of this law. Against this background, particular attention was paid to the construction of the special state as a (separate and independent) institution of material administrative law, as well as to issues concerning, inter alia, administrative regulations, general administrative acts, administrative enforcement of non-pecuniary obligations, administrative proceedings, criminal-administrative law, and social (digital) exclusion in administrative law. The considerations are summed up by the statement that administrative law – both in practical and theoretical terms – has turned out to be insufficiently prepared for an epidemic of an infectious disease in general, and even more so for an epidemic of a scale such as that caused by the SARS-CoV-2 coronavirus.

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