Literature DB >> 32382166

Significant Applications of Big Data in COVID-19 Pandemic.

Abid Haleem1, Mohd Javaid1, Ibrahim Haleem Khan2, Raju Vaishya3.   

Abstract

Entities:  

Year:  2020        PMID: 32382166      PMCID: PMC7204193          DOI: 10.1007/s43465-020-00129-z

Source DB:  PubMed          Journal:  Indian J Orthop        ISSN: 0019-5413            Impact factor:   1.251


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Dear Editor, New cases of COVID-19 (Coronavirus) are increasing rapidly at astonishing rates globally; more than 1.2 billion people have developed an infection and out of these, around 65,000 have died of this disease, until today. This immediate burst of cases and their health data have created a vital source of information and knowledge. There is an immediate requirement to store such a large amount of data of these cases, using different data storage technologies. These data are used to undertake research and development about the virus, pandemic and measures to fight this virus and its after-effects. Big data is an innovative technology which can digitally store a large amount of data of these patients. It helps to computationally analyse to reveal patterns, trends, associations and differences. It can also help in revealing the insights into the spread and control of this virus. With detailed data capturing capability, big data can be used gainfully to minimise the risk of spreading this virus [1, 2]. Big data technology can store a massive amount of information about these people infected with this COVID-19 virus. It helps in understanding the nature of this virus in detail. The data obtained can further be trained over again for developing future preventive methods. This technology is used to store the data of all types of cases (infected, recovered and expired) affected by COVID-19. This information can be effectively used for case identification and helping to allocate the resources for better protection of public health [3, 4].Several modalities of digital data including patient location, proximity, patient-reported travel, co-morbidity, patient physiology and current symptoms can be digitised and used for generating actionable insights at both community and demography levels. Table 1 provides significant applications of big data in COVID-19 pandemic.
Table 1

Significant applications of big data in COVID-19 pandemic

S. No.ApplicationsDescription
1Identification of infected cases

It is capable of storing the complete medical history of all patients, due to its capability of storing a massive amount of data

By providing the captured data, this technology helps in identification of the infected cases and undertake further analysis of the level of risks

2Travel history

Used to store the travel history of the people to analyse the risk

Helps to identify people who may be in contact with the infected patient of this virus

3Fever symptoms

Big data can keep the record of fever and other symptoms of a patient and suggest if medical attention is required

Helps to identify the suspicious cases and other misinformation with the appropriate data

4Identification of the virus at an early stage

Quickly helps to identify the infected patient at an early stage

Helps to analyse and identify persons who can be infected by this virus in future

5Identification and analysis of fast-moving disease

Helps to effectively analyse the fast-moving disease as efficiently as possible

Potential to handle appropriate information regarding the disease

6Information during lockdown

This technology collects information regarding this virus during the lockdown

Track and monitor the movement of people and entire health management

7People entered or leaving the affected area

It helps to analyse the number of people entered or leaving from the affected city

With these vast amount of data, health specialist can quickly identify the chances of the virus in those peoples

8Faster development of medical treatments

Assist in fast-tracking the development of new medicines and equipment needed for current and future medicinal needs

Provides previous data of virus inhabited or spread and, thus, helps in gaining a giving advantage over newer pandemic/epidemic with previously analysed results

Significant applications of big data in COVID-19 pandemic It is capable of storing the complete medical history of all patients, due to its capability of storing a massive amount of data By providing the captured data, this technology helps in identification of the infected cases and undertake further analysis of the level of risks Used to store the travel history of the people to analyse the risk Helps to identify people who may be in contact with the infected patient of this virus Big data can keep the record of fever and other symptoms of a patient and suggest if medical attention is required Helps to identify the suspicious cases and other misinformation with the appropriate data Quickly helps to identify the infected patient at an early stage Helps to analyse and identify persons who can be infected by this virus in future Helps to effectively analyse the fast-moving disease as efficiently as possible Potential to handle appropriate information regarding the disease This technology collects information regarding this virus during the lockdown Track and monitor the movement of people and entire health management It helps to analyse the number of people entered or leaving from the affected city With these vast amount of data, health specialist can quickly identify the chances of the virus in those peoples Assist in fast-tracking the development of new medicines and equipment needed for current and future medicinal needs Provides previous data of virus inhabited or spread and, thus, helps in gaining a giving advantage over newer pandemic/epidemic with previously analysed results Big data provides a massive amount of information to the scientists, health workers, epidemiologists and help them to make informed decision to fight with the COVID-19 virus. These data can be used to track the virus on a global basis continuously and to create innovation in the medical field [5, 6]. It can help to forecast the impact of COVID-19 in a particular area and the whole population. It helps in research and development of new treatment procedure. Big data can also provide possible sources and opportunities for the people and, thus, help to handle the stressful situation. Overall, this technology provides data to undertake analysis of the disease transmission, movement, and health monitoring and prevention system. In the surgical speciality of Orthopaedics, the big data can help in the predictive analysis of Orthopaedic and Trauma surgery, from the available data. Trauma mortality and morbidity mimic the current pandemic, and there may be cross-fertilisation of ideas from it. This technology is helpful in keeping record of the orthopaedic patients, which can influence positive and correct clinical decision-making. It can, therefore, increase the performance by a better understanding of the treatment procedures from the appropriate captured data. Big data is a blessing for conducting the clinical trials, to speed up the treatment process by analysing the patient’s record. Big data analytics will act as a medium for tracking, controlling, research and prevention of COVID-19 as a pandemic. It will diversify manufacturing, enhance vaccine development on more profound means, with absolute knowledge. Prevalent modelled data helps in understanding and offering an edge over the other process like corresponding homology models predicted by fold and function assignment system server for each target protein were downloaded from Protein Data Bank, for predicting the COVID-19 cure and identifying the symptoms associated with it [7, 8]. Big data provides the insights and analyses with the factors leading to better containment of the infected persons. China suppressed the COVID-19 with the help of data collection and implementing it with AI leading towards a low rate of spread. There are several big data components to this pandemic where AI can play a significant role like in biomedical research, natural language processing, social media, and mining the scientific literature. The surgical specialty of Orthopaedics requires excellent surgical skills, clinical acumen, reasonable physical strength and better understanding. As a complement to these requirements, new technologies (e.g., AI) have been are adopted in the last few years, which has helped to create innovations in the field of Orthopaedics and has also provided positive impact in the treatment and surgery [9]. Significant changes and innovations are possible with the help of new technologies like big data, AI and 3D printing. These technologies provide opportunities for better service and patient outcomes [10]. In some places, the big data provides information to identify the suspected cases of this virus. It helps to provide an efficient way to prevent the illness and extract other valuable information. In future, big data will help the public, doctors, other healthcare professionals and researchers to track this virus and analyse the infection mechanism of COVID-19. Data provided help to examine how this infection can be slowed or eventually prevented, and help to optimise the allocation of resources and accordingly contributing to taking appropriate and timely decisions. With the assistance of this digital data storing technology, doctors and scientists can also develop a convenient and efficient method of COVID-19 testing.
  7 in total

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3.  Towards robust diagnosis of COVID-19 using vision self-attention transformer.

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Review 4.  Data for orthopaedic surgeons - A review.

Authors:  Srinivas B S Kambhampati; Karthik Vishwanathan; Mohit Kumar Patralekh; Raju Vaishya
Journal:  J Clin Orthop Trauma       Date:  2021-07-15

5.  Big data directed acyclic graph model for real-time COVID-19 twitter stream detection.

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6.  Impact of COVID 19 Pandemic and Big Data on China's International Trade: Challenges and Countermeasures.

Authors:  Shuang Zhao
Journal:  Front Public Health       Date:  2022-06-09

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

Authors:  Jun Wu; Jian Wang; Stephen Nicholas; Elizabeth Maitland; Qiuyan Fan
Journal:  J Med Internet Res       Date:  2020-10-09       Impact factor: 5.428

  7 in total

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