Big data for human security: The case of COVID-19

Cárdenas，Pedro1; Ivrissimtzis，Ioannis1; Obara，Boguslaw2; Kureshi，Ibad3; Theodoropoulos，Georgios4

2022-04-01

10.1016/j.jocs.2022.101574

Journal of Computational Science   影响因子和分区

1877-7503

1877-7511

The COVID-19 epidemic has changed the world dramatically since societies are changing their behaviour according to the new normal, which comes along with numerous challenges and uncertainties. These uncertainties have led to instabilities in several facets of society, most notably health, economy and public order. Measures to contain the pandemic by governments have occasionally met with increasing discontent from societies and have triggered social unrest, imposing serious threats to human security. Big Data Analytics can provide a powerful force multiplier to support policy and decision makers to contain the virus while at the same time dealing with such threats to human security. This paper presents the utilisation of a big data forecasting and analytics framework and its utilisation to deal with COVID-19 triggered social unrest. The paper is an extended version of paper Cárdenas et al. (2021) presented at the 2021 International Conference on Computational Science.

Big data COVID-19 Data analytics Epidemics Human security Machine learning

SCI ; EI

英语

其他

CONACyT, Mexico[390255] ; Guangdong Province Innovative and Entrepreneurial Team Programme, China[2017ZT07X386] ; Shenzhen Peacock Pro-gramme, China[Y01276105]

Computer Science

Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods

WOS:000777304100007

ELSEVIER

20220811690551

Advanced Analytics ; Big data ; Decision making ; Machine learning ; Viruses

Biology:461.9 ; Data Processing and Image Processing:723.2 ; Artificial Intelligence:723.4 ; Management:912.2

2-s2.0-85124883450

Scopus

1.Dept. Computer Science,Durham University,United Kingdom
2.School of Computing,Newcastle University,United Kingdom
3.HM Land Registry,Durham,United Kingdom
4.Dept. Computer Science and Engineering,Southern University of Science and Technology (SUSTech),Shenzhen,China

Cárdenas，Pedro,Ivrissimtzis，Ioannis,Obara，Boguslaw,et al. Big data for human security: The case of COVID-19[J]. Journal of Computational Science,2022,60.

Cárdenas，Pedro,Ivrissimtzis，Ioannis,Obara，Boguslaw,Kureshi，Ibad,&Theodoropoulos，Georgios.(2022).Big data for human security: The case of COVID-19.Journal of Computational Science,60.

Cárdenas，Pedro,et al."Big data for human security: The case of COVID-19".Journal of Computational Science 60(2022).